The Internet of Things (IoT) is an interface with the physical world that usually operates in
random-sparse-event (RSE) scenarios. This article discusses main challenges of IoT chips …

The von Neumann bottleneck and memory wall have posed fundamental limitations in
latency and energy consumption of modern computers based on von Neumann architecture …

Aside from some living tissues, few materials can autonomously learn to exhibit desired
behaviors as a consequence of prolonged exposure to unanticipated ambient loading …

Processing-using-DRAM (PUD) is a processing-in-memory (PIM) approach that uses a
DRAM array's massive internal parallelism to execute very-wide (eg, 16,384-262,144-bit …

Bulk bitwise operations, ie, bitwise operations on large bit vectors, are prevalent in a wide
range of important application domains, including databases, graph processing, genome …

To combat the high energy costs of moving data between main memory and the CPU, recent
works have proposed to perform processing-using-memory (PUM), a type of processing-in …

The rapid growth of the Internet of Things (IoTs) has resulted in an explosive increase in
data, and thus has raised new challenges for data processing units. Edge computing, which …

SRAM based computing-in-memory (SRAM-CIM) techniques have been widely studied for
neural networks (NNs) to solve the “Von Neumann bottleneck”. However, as the scale of the …

In this paper, we devise and optimize schemes for the resistive random-access memory
(RRAM)-based hardware implementation of convolutional neural networks (CNNs). The key …

Memory-centric computing aims to enable computation capability in and near all places
where data is generated and stored. As such, it can greatly reduce the large negative …